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This dynamic chart analyzes the stock price of the FANG stocks from Jan 1st 2000 to Dec 31st 2016. This is a time series chart and the data source is FANG dataset from tidyquant package.
library(plotly)
library(tidyverse)
library(tidyquant)
library(ggplot2)
data("FANG")
AMZN <- tq_get("AMZN", get = "stock.prices", from = "2000-01-01", to = "2016-12-31")
p <- AMZN %>%
ggplot(aes(x = date, y = adjusted)) +
geom_line(color = palette_light()[[1]]) +
scale_y_continuous() +
labs(title = "AMZN Line Chart",
subtitle = "Continuous Scale",
y = "Closing Price", x = "") +
theme_tq()
ggplotly(p, tooltip = c("symbol"))GOOG <- tq_get("GOOG", get = "stock.prices", from = "2000-01-01", to = "2016-12-31")
p <- GOOG %>%
ggplot(aes(x = date, y = adjusted)) +
geom_line(color = palette_light()[[2]]) +
scale_y_continuous() +
labs(title = "GOOG Line Chart",
subtitle = "Continuous Scale",
y = "Closing Price", x = "") +
theme_tq()
ggplotly(p)FB <- tq_get("FB", get = "stock.prices", from = "2000-01-01", to = "2016-12-31")
p <- FB %>%
ggplot(aes(x = date, y = adjusted)) +
geom_line(color = palette_light()[[3]]) +
scale_y_continuous() +
labs(title = "FB Line Chart",
subtitle = "Continuous Scale",
y = "Closing Price", x = "") +
theme_tq()
ggplotly(p)NFLX <- tq_get("NFLX", get = "stock.prices", from = "2000-01-01", to = "2016-12-31")
p <- NFLX %>%
ggplot(aes(x = date, y = adjusted)) +
geom_line(color = palette_light()[[4]]) +
scale_y_continuous() +
labs(title = "NFLX Line Chart",
subtitle = "Continuous Scale",
y = "Closing Price", x = "") +
theme_tq()
ggplotly(p)